IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v349y2023ics0306261923010103.html
   My bibliography  Save this article

Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology

Author

Listed:
  • Zhou, Yuan
  • Wang, Jiangjiang
  • Yang, Mingxu
  • Xu, Hangwei

Abstract

Developing hybrid renewable energy multi-energy system at the community level (CMES) is crucial for sustainable development and society. There are considerable resources in community users that can be activated by demand-side management (DSM) and combined with CMES for smart and clean energy supplies. This work focuses on optimal multi-timescale CMES management at energy and power levels considering source-load interaction. Firstly, the flexible community building and EV loads are comprehensively modeled, including the subjective psychological factors of community users' willingness to participate in DSM activities. Then, a bilevel collaborative strategy is proposed to manage CMES. The upper-level unites all schedulable resources to actively control CMES and flexible loads to achieve optimal multi-energy balances. The lower-level forms hybrid virtual electrical storage to passively adapt to instantaneous power rebound/decline events. These two levels are bridged through chance-constrained programming, achieving risk avoidance. Finally, the performances, including community users, the grid, and CMES itself, are evaluated, as well as influences of confidence level and user attitudes (in DSM activities). Simulation results show that the proposed strategy with a high confidence level avoids the lack of flexibility and load interruption and reduces cost and grid interaction fluctuations by 5.75 % and 59.48 %, respectively. DSM can support the efficient and flexible operation of CMES by providing equivalent energy storage with a capacity/power of up to 657 kWh/350 kW. On the other hand, the high subsidy price reduces CMES's interests, and users' benefits will be weakened accordingly, while users actively involved in DSM create a win-win situation with CMES.

Suggested Citation

  • Zhou, Yuan & Wang, Jiangjiang & Yang, Mingxu & Xu, Hangwei, 2023. "Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology," Applied Energy, Elsevier, vol. 349(C).
    • Handle: RePEc:eee:appene:v:349:y:2023:i:c:s0306261923010103
    DOI: 10.1016/j.apenergy.2023.121646
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923010103
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.121646?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hossain, Md Alamgir & Pota, Hemanshu Roy & Squartini, Stefano & Zaman, Forhad & Guerrero, Josep M., 2019. "Energy scheduling of community microgrid with battery cost using particle swarm optimisation," Applied Energy, Elsevier, vol. 254(C).
    2. Ouyang, Tiancheng & Zhang, Mingliang & Wu, Wencong & Zhao, Jiaqi & Xu, Hua, 2023. "A day-ahead planning for multi-energy system in building community," Energy, Elsevier, vol. 267(C).
    3. Li, Peng & Wang, Zixuan & Wang, Jiahao & Guo, Tianyu & Yin, Yunxing, 2021. "A multi-time-space scale optimal operation strategy for a distributed integrated energy system," Applied Energy, Elsevier, vol. 289(C).
    4. Wang, Jiangjiang & Han, Zepeng & Guan, Zhimin, 2020. "Hybrid solar-assisted combined cooling, heating, and power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    5. Bartolini, Andrea & Carducci, Francesco & Muñoz, Carlos Boigues & Comodi, Gabriele, 2020. "Energy storage and multi energy systems in local energy communities with high renewable energy penetration," Renewable Energy, Elsevier, vol. 159(C), pages 595-609.
    6. Zhu, Xu & Sun, Yuanzhang & Yang, Jun & Dou, Zhenlan & Li, Gaojunjie & Xu, Chengying & Wen, Yuxin, 2022. "Day-ahead energy pricing and management method for regional integrated energy systems considering multi-energy demand responses," Energy, Elsevier, vol. 251(C).
    7. Li, Haoran & Zhang, Chenghui & Sun, Bo, 2022. "Deep integration planning of sustainable energies in district energy system and distributed energy station," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    8. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
    9. Houben, Nikolaus & Cosic, Armin & Stadler, Michael & Mansoor, Muhammad & Zellinger, Michael & Auer, Hans & Ajanovic, Amela & Haas, Reinhard, 2023. "Optimal dispatch of a multi-energy system microgrid under uncertainty: A renewable energy community in Austria," Applied Energy, Elsevier, vol. 337(C).
    10. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & Mazzotti, Marco & McKenna, Russell, 2023. "Designing residential energy systems considering prospective costs and life cycle GHG emissions," Applied Energy, Elsevier, vol. 331(C).
    11. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    12. Yang, Wenjun & Guo, Jia & Vartosh, Aris, 2022. "Optimal economic-emission planning of multi-energy systems integrated electric vehicles with modified group search optimization," Applied Energy, Elsevier, vol. 311(C).
    13. Li, Peng & Wang, Zixuan & Yang, Weihong & Liu, Haitao & Yin, Yunxing & Wang, Jiahao & Guo, Tianyu, 2021. "Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game," Energy, Elsevier, vol. 214(C).
    14. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    15. Zhou, Yuan & Wang, Jiangjiang & Liu, Yi & Yan, Rujing & Ma, Yanpeng, 2021. "Incorporating deep learning of load predictions to enhance the optimal active energy management of combined cooling, heating and power system," Energy, Elsevier, vol. 233(C).
    16. Xu, Da & Yuan, Zhe-Li & Bai, Ziyi & Wu, Zhibin & Chen, Shuangyin & Zhou, Ming, 2022. "Optimal operation of geothermal-solar-wind renewables for community multi-energy supplies," Energy, Elsevier, vol. 249(C).
    17. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    18. Li, Ke & Ye, Ning & Li, Shuzhen & Wang, Haiyang & Zhang, Chenghui, 2023. "Distributed collaborative operation strategies in multi-agent integrated energy system considering integrated demand response based on game theory," Energy, Elsevier, vol. 273(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Yuan & Wang, Jiangjiang & Wei, Changqi & Li, Yuxin, 2024. "A novel two-stage multi-objective dispatch model for a distributed hybrid CCHP system considering source-load fluctuations mitigation," Energy, Elsevier, vol. 300(C).
    2. Jiang, Meihui & Xu, Zhenjiang & Zhu, Hongyu & Hwang Goh, Hui & Agustiono Kurniawan, Tonni & Liu, Tianhao & Zhang, Dongdong, 2024. "Integrated demand response modeling and optimization technologies supporting energy internet," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    3. Li, Li & Fan, Shuai & Xiao, Jucheng & Zhou, Huan & Shen, Yu & He, Guangyu, 2024. "Fair trading strategy in multi-energy systems considering design optimization and demand response based on consumer psychology," Energy, Elsevier, vol. 306(C).
    4. Han, Fengwu & Zhao, Yunlong & Zeng, Jianfeng & Zhang, Shengnan & Wu, Tianyu, 2024. "Uncertain parameters adjustable two-stage robust optimization of a rural housing integrated energy system considering biomass on-site utilization," Energy, Elsevier, vol. 296(C).
    5. Yong Cui & Jian Zheng & Wenying Wu & Kun Xu & Desen Ji & Tian Di, 2024. "Framework and Outlooks of Multi-Source–Grid–Load Coordinated Low-Carbon Operational Systems Considering Demand-Side Hierarchical Response," Energies, MDPI, vol. 17(23), pages 1-20, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Yuan & Wang, Jiangjiang & Wei, Changqi & Li, Yuxin, 2024. "A novel two-stage multi-objective dispatch model for a distributed hybrid CCHP system considering source-load fluctuations mitigation," Energy, Elsevier, vol. 300(C).
    2. Fan, Wei & Tan, Zhongfu & Li, Fanqi & Zhang, Amin & Ju, Liwei & Wang, Yuwei & De, Gejirifu, 2023. "A two-stage optimal scheduling model of integrated energy system based on CVaR theory implementing integrated demand response," Energy, Elsevier, vol. 263(PC).
    3. Xu, Xun & Shao, Zhenguo & Chen, Feixiong & Cheng, Guoyang, 2024. "Multi-game optimization operation strategy for integrated energy system considering spatiotemporal correlation of renewable energy," Energy, Elsevier, vol. 303(C).
    4. Zhang, Zhaoyan & Jiang, Ping & Liu, Zhibin & Fu, Lei & Wang, Peiguang, 2023. "Capacity optimal configuration and collaborative planning of multi-region integrated energy system," Energy, Elsevier, vol. 278(PB).
    5. Zhou, Yuan & Wang, Jiangjiang & Li, Yuxin & Wei, Changqi, 2023. "A collaborative management strategy for multi-objective optimization of sustainable distributed energy system considering cloud energy storage," Energy, Elsevier, vol. 280(C).
    6. Li, Li & Fan, Shuai & Xiao, Jucheng & Zhou, Huan & Shen, Yu & He, Guangyu, 2024. "Fair trading strategy in multi-energy systems considering design optimization and demand response based on consumer psychology," Energy, Elsevier, vol. 306(C).
    7. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    8. Liu, Jiejie & Li, Yao & Ma, Yanan & Qin, Ruomu & Meng, Xianyang & Wu, Jiangtao, 2023. "Two-layer multiple scenario optimization framework for integrated energy system based on optimal energy contribution ratio strategy," Energy, Elsevier, vol. 285(C).
    9. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    10. Zheng, Ling & Zhou, Bin & Cao, Yijia & Wing Or, Siu & Li, Yong & Wing Chan, Ka, 2022. "Hierarchical distributed multi-energy demand response for coordinated operation of building clusters," Applied Energy, Elsevier, vol. 308(C).
    11. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    12. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).
    13. Wang, Haibing & Zhao, Anjie & Khan, Muhammad Qasim & Sun, Weiqing, 2024. "Optimal operation of energy hub considering reward-punishment ladder carbon trading and electrothermal demand coupling," Energy, Elsevier, vol. 286(C).
    14. Wang, Liying & Lin, Jialin & Dong, Houqi & Wang, Yuqing & Zeng, Ming, 2023. "Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system," Energy, Elsevier, vol. 270(C).
    15. Jiang, Meihui & Xu, Zhenjiang & Zhu, Hongyu & Hwang Goh, Hui & Agustiono Kurniawan, Tonni & Liu, Tianhao & Zhang, Dongdong, 2024. "Integrated demand response modeling and optimization technologies supporting energy internet," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    16. Li, Ke & Ye, Ning & Li, Shuzhen & Wang, Haiyang & Zhang, Chenghui, 2023. "Distributed collaborative operation strategies in multi-agent integrated energy system considering integrated demand response based on game theory," Energy, Elsevier, vol. 273(C).
    17. Lv, Chaoxian & Liang, Rui & Zhang, Ge & Zhang, Xiaotong & Jin, Wei, 2023. "Energy accommodation-oriented interaction of active distribution network and central energy station considering soft open points," Energy, Elsevier, vol. 268(C).
    18. Ma, Xin & Peng, Bo & Ma, Xiangxue & Tian, Changbin & Yan, Yi, 2023. "Multi-timescale optimization scheduling of regional integrated energy system based on source-load joint forecasting," Energy, Elsevier, vol. 283(C).
    19. Ren, Fukang & Lin, Xiaozhen & Wei, Ziqing & Zhai, Xiaoqiang & Yang, Jianrong, 2022. "A novel planning method for design and dispatch of hybrid energy systems," Applied Energy, Elsevier, vol. 321(C).
    20. Ma, Lan & Xie, Lirong & Ye, Jiahao & Bian, Yifan, 2024. "Two-stage dispatching strategy for park-level integrated energy systems based on a master-slave-cooperative hybrid game model," Renewable Energy, Elsevier, vol. 232(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:349:y:2023:i:c:s0306261923010103. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.